NF X06-037
Application of statistical methods - Aptitude of a multimodal production process
Le présent document définit une méthodologie permettant d'évaluer l'aptitude d'un processus de production sur le court terme à respecter une caractéristique mesurable tolérancée du produit, même si des causes identifiées induisent une distribution multimodale.
Le présent document définit une méthodologie permettant d'évaluer l'aptitude d'un processus de production sur le court terme à respecter une caractéristique mesurable tolérancée du produit, même si des causes identifiées induisent une distribution multimodale.
ISO 22514-8:2014 aims to define the evaluation method to quantify the short-term capability of a production process (capacity of the production tool, widely termed capability), i.e. the machine performance index, to ensure compliance to a toleranced measurable product characteristic, when said process does not feature any kind of sorting system. If the production process integrates a sorting system, then this one (clearing away nonconforming parts) should be analysed independently. ISO 22514-8:2014 does not aim to define evaluation methods of the capability of a production process that is gauged through long-term observation (capability process or performance process indices). ISO 22514-8:2014 defines the principles guiding the development of indicators for quantifying capability, and the statistical methods to be employed. The characteristics used to evaluate production process capability have statistical distributions, and it is presumed, a priori, that at least one of these distributions is multi-modal. A distribution is presumed to be multimodal if it results from the marked effect of at least one cause inducing a significant difference between the produced items. ISO 22514-8:2014 applies, for example, to characteristics generated by processes such as the following: multi-cavity casting, multi-fixture machining, batch load treatments. Each cavity, fixture, or position in the batch load corresponds to a different state. The multi-state process can be understood as the result of the combination of different states within the same process (e.g. cavity, fixture, position in the batch load).
- Avant-propos4
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1 Domaine d'application4
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2 Références normatives4
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3 Termes et définitions5
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4 Symboles et abréviations9
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5 Analyse technique préalable du processus9
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5.1 Généralités9
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5.2 Identification des facteurs intrinsèques10
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5.3 Détermination des modes particuliers du processus10
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6 Vérifications préalables au calcul d'indicateurs10
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6.1 Moyen de mesure10
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6.2 Définition du plan d'échantillonnage pour estimer la dispersion intrinsèque globale11
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7 Estimation de la dispersion intrinsèque globale et calcul des indicateurs d'aptitude11
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7.1 Généralités11
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7.2 Vérification de l'absence de valeur aberrante parmi les mesures effectuées12
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7.3 Détermination des largeurs des dispersions intrinsèques locales12
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7.4 Détermination des positions des dispersions intrinsèques locales13
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7.5 Dispersion intrinsèque globale : type et estimation14
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7.6 Calcul des indicateurs d'aptitude Car, et Cmk (ou Pp et Ppk)16
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7.7 Seuils d'acceptation des indicateurs d'aptitude17
- Annexe A (informative) Modes de qualification d'un processus de traitement18
- Annexe B (normative) Tests statistiques32
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